The performance and reliability of medium voltage electricity distribution feeders has a significant impact on the quality of service offered by electric utility companies to their commercial, industrial, and residential customers. To that end, reliability of the service and continuity of supply sit on top of every utility's business objectives. Electrical outages, service disruptions, and grid disturbances are however inevitable. They do occur and they are costly to the utility and the society alike. A recent study performed by Lawrence Berkeley National Laboratory in the United States reports that unreliable electrical systems cost $80BUSD annually due to mainly large number of short disturbances. When interruptions occur, the utility's top priority is to address the outages as quickly as possible and restore the power to as many customers as possible.
The effectiveness of all network operations, particularly outage management, depends heavily on availability of information systems that deliver the right information to the right operator at the right time.
Asset failures and faults resulting in interruptions as well as normal network operations manifest themselves in voltage and current excursions which are called events. These events are captured by Intelligent Electronic Devices (IEDs) as raw data. The recorded raw waveforms are seldom utilized for real-time and accurate decision making due to the lack of time, resources, and appropriate tools.
In order to improve the controllability and reliability of electrical networks, increasing number of measurement points and various kinds of intelligent electrical devices are installed. Often times, there is a redundancy in data as for example IEDs electrically connected to the same bus may capture multiple manifestations of a single event.
Microprocessor-based digital systems including protection IEDs and sensors used in distribution networks produce a lot of raw data that need to be analysed and processed for various decisions making functions ranging from protection to monitoring to control actions. Most often, the digital systems are put in place to replace the legacy electromechanical systems and configured to deliver the same functionalities as their legacy counterparts did. As such, advanced data-based methods and decision support tools are not widely used leading to a substantial underutilization of digital data. In the midst of rising data volumes and shrinking engineering work force, it is increasingly infeasible for the grid operators to deal with this “data tsunami” and make an effective use of the data that is often correlated and redundant.
In particular, the raw data captured by IEDs as disturbance records are rarely of direct benefit beyond their occasional use by protection engineers. Traditionally, the analysis is strictly a manual process. One or more analysts would become familiar with the data and, with the help of statistical techniques, provide summaries and generate reports. However, such an approach is rapidly breaking down as the volume of the data grows so fast that manual analysis, even if possible, simply cannot keep pace.